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AI Use cases in Healthcare:
From Idea to Implementation
Swathi Young
CTO, Integrity Management Services, Inc.
IntegrityM.com
@swathiyoung
2
What is AI?
The term was coined by John
McCarthy in 1956 and it means
“is intelligence demonstrated
by machines, in contrast to
the natural
intelligence displayed by
humans. It is an umbrella term
whose sub-fields range from
robotics to machine learning.”
Artificial Intelligence
3
4
Machine Learning
AI that uses algorithms that automatically “learns” without being explicitly programmed.
Machine learning is the application of AI techniques using statistical methods
Genre
Award
x
y
Sci-Fi Drama
Golden
Globes
Oscars
x x x
x x x x
x x x
x x x x
x x
x x x x x x
o
?
5
Supervised and Unsupervised learning
6
TO GET STARTED
1. BUSINESS CASE
2. DATA
3. ML MODELS
7
KEY ACTIVITIES FOR ENTERPRISE AI ADOPTION
8
Key steps of implementation of a use case
Business
Objective
Data
Sources
Data
Analysis/
Feature
Engg.
Training
DataSet
Validation/
Test
Dataset
Evaluation
Model Deploy
Visualize
Output
Pre-Processing Modeling Outcomes
Business rules
9
USE CASES
10
PREDICTIVE
ANALYTICS
11
CELL-BASED DISEASED MODELS
Source: Insitro.com
12
TEXT ANALYSIS
13
NLP Analysis
Source: Healthcatalyst.com
14
IMAGE
ANALYSIS
15
MEDICAL IMAGES
16
KEY CHALLENGES
Bias Responsibility
Transparency
ETHICS
BUILDING
TRUST
17
THANK YOU
18
Connect with me on LinkedIn and Twitter
@Swathiyoung
YouTube channel – Trendy Techie
THANK YOU!

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Ai idea to implementation : Use cases in Healthcare

Hinweis der Redaktion

  1. Dubai robo cop
  2. Machine Learning to learn to tell fraudsters from legitimate users without explicitly telling it what designates to look for. Let’s dive deeper… The idea is that there are certain characteristics of fraudulent transactions that differentiate them from legitimate ones. Machine Learning algorithms recognize patterns in the data that allow them to discern fraudsters from legitimate clients, based on thousands of pieces of information, that sometimes may seem completely unrelated to a human being. The algorithm is searching for patterns in fraudsters’ behavior, their hardware characteristics etc.